Section: Lectures | Text Analytics 2019 | INF - e-learning

Section outline

Date	Topic	Material
16/09/2019	Introduction
17/09/2019	Introduction to Probability	slides
24/09/2019	Language Modeling	slides
26/09/2019	Language Modeling
30/09/2019	Python Tutorial	See notebooks: Introduction to Python and Introduction to Python 2.
01/10/2019	Python Tutorial and Examples
03/10/2019	Building Language Models	See notebook: Language Models
08/10/2019	Introduction to NLTK	See notebook: Introduction to NLTK
10/10/2019	Representation of Words	slides
15/10/2019	Word Embeddings: Word2Vec, GloVE, FastText, ELMo	See notebook: Language Models
17/10/2019	Text Classification	slides
22/10/2019	Classifiers	slides
24/10/2019	Sequence Labeling	slides
29/10/2019	Named Entity Recognition	slides
31/10/2019	Deep Learning	slides Notebook: Introduction to eras
05/11/2019	Neural Language Models	slides Notebook: DocumentEmbeddings.ipynb
07/11/2019	Transformer models	slides
12/11/2019	Parsing	slides
14/11/2019	Deep Learning for NLP
19/11/2019	Deep Learning for NLP
21/11/2019	Introduction to Sentiment Analysis	slides
26/11/2019	Lexical Resources	slides Notebook: pmi-lex-IMDB.ipynb
28/11/2019	Sentiment Classification	slides Notebook: VADER.ipynb Classification sklearn.ipynb
03/12/2019	Sentiment Classification	Notebook: Classification sklearn-feats.ipynb Classification - lstmNet.ipynb Classification - cnnNet.ipynb
05/12/2019	Transfer Learning/Opinion Extraction	slides
10/12/2019	Quantification	slides
12/12/2019	Spam Detection: mail spam & phishing, web spam, review spam	slides